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Spatial Microsimulation and Policy Analysis

Spatial Microsimulation and Policy Analysis. Robert Tanton. (CRICOS) #00212K. Outline. Description of spatial microsimulation Applications of spatial microsimulation Future of spatial microsimulation Further reading. (CRICOS) #00212K. The need for spatial microsimulation.

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Spatial Microsimulation and Policy Analysis

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  1. Spatial Microsimulation and Policy Analysis Robert Tanton (CRICOS) #00212K

  2. Outline • Description of spatial microsimulation • Applications of spatial microsimulation • Future of spatial microsimulation • Further reading (CRICOS) #00212K

  3. The need for spatial microsimulation • Policy makers want small area estimates • Ex Social Inclusion Unit – spatial estimates are one of priorities • “Communities” of interest (CRICOS) #00212K

  4. Collecting small area information

  5. Applications of spatial microsimulation • Small area indicators in a cross-tabulation • Poverty rates for older people living alone • Used to inform policy on service provision to small areas • Projections • Use ABS small area population projections and Treasury labour force projections to apply changes in demographics • Derive projections of service populations for policy makers • Small area effects of a policy change • Model national policy change using STINMOD Tax/Transfer model • Model national change using a CGE model and a Tax/Transfer microsimulation model • Look at effect for each area using regional weights (CRICOS) #00212K

  6. Small area indicators of poverty • For older people living alone

  7. What are the poverty rates for older people living alone?

  8. Projections • Projections of key variables for small areas • Using population and labour force projections from Commonwealth • Regression for each of the benchmark tables to get projected benchmarks • Reweight survey data to projected benchmarks • Examples – Where childcare places are going to be needed in future; where aged care places are going to be needed in future

  9. Growth from 2006 – 2027 in the number of 3 – 4 year old children with all parents working, Queensland

  10. Small area policy analysis • Small area policy analysis • Link to NATSEM’s tax/transfer microsimulation model – uses same datasets • Spatial weights linked to STINMOD to get small area effects of STINMOD modelling • Examples – Small area effects of changes in tax or transfer system; Small area effect of the 2014 Budget

  11. Small Area Policy Analysis • Small area effects of changes in transfer system • Change to FTB Income tapers • First income taper reduced from 20 to 10 per cent; second left at 30 per cent

  12. Spatial Effect of a change to FTB

  13. Small Area reduction in incomes in 2017-18 as a result of the 2014-15 Budget

  14. Small area policy analysis • Link between CGE model, STINMOD and SpatialMSM • CGE model provides national change in incomes by industry; STINMOD applies this to individuals in each industry; SpatialMSM regionalises STINMOD • Effect of a change in the Terms of Trade • Boomed from 2009 to 2011 but decreasing from 2011 to Dec 2013 (when this analysis was done) • What is the spatial effect?

  15. Small area effect of a change in the Terms of Trade

  16. Limitations of spatial microsimulation • Limits to what variables can extract reliably • Limitations due to benchmarking process • Validation difficult • Difficult to calculate confidence intervals • Ongoing work at NATSEM

  17. The future of spatial microsimulation • Synthetic populations for an entire country • Already done for Japan 127.3 million people • Looking at doing at NATSEM for indicators of individual level disadvantage • Add confidence intervals • Work being done at the moment at NATSEM • Add dynamic elements • Better projections • Very data intensive – longer term NATSEM project

  18. The future of spatial microsimulation • Decision Support Systems • Resource limited demographic projection • ABS - 650,000 people in ACT by 2056 • Really? Where are they going to live? How many jobs will we need? How much water? Electricity? Transport? • Help planners to make planning decisions • Recent paper on modelling decision support system using SpatialMSM went to US Regional Science conference • Book chapter soon

  19. Further Reading • Policy modelling • Harding, Vu, Tanton and Vidyattama (2009). “Improving Work Incentives and Incomes for Parents: The National and Geographic Impact of Liberalising the Family Tax Benefit Income Test.” Economic Record 85 (s1): S48–S58. • Vidyattama, Rao and Tanton (2014). “Modelling the Impact of Declining Australian Terms of Trade on the Spatial Distribution of Income.” International Journal of Microsimulation 7: 100–126. • Projections • Harding, Vidyattama and Tanton (2011). “Demographic Change and the Needs-Based Planning of Government Services: Projecting Small Area Populations Using Spatial Microsimulation.” Journal of Population Research 28: 203–224. • Spatial Microsimulation • Tanton and Edwards (2013). Spatial Microsimulation: A Reference Guide for Users. Edited by Robert Tanton and Kimberley Edwards. Springer Netherlands. • Tanton (2011). “Spatial Microsimulation as a Method for Estimating Different Poverty Rates in Australia.” Population, Space and Place 17 (3): 222–235. • Tanton (2014). “A Review of Spatial Microsimulation Methods.” International Journal of Microsimulation 7 (1): 4–25. (CRICOS) #00212K

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